基于改进ICP算法的叶片型线轮廓度误差评定

Blade Profile Profile Error Evaluation Based on Improved ICP Algorithm

针对传统最近迭代点(ICP)算法存在配准精度较低的问题进行算法改进。首先,考虑到三坐标测量机测量数据呈现有序排列、且一一对应的特点,使用了一种基于矢量对齐法的型线数据初配准方法进行初配准;其次,在传统ICP算法配准的基础上,对待配准数据进行非均匀有理化B样条(NURBS)曲线拟合,再利用自适应粒子群算法对测量数据进一步精配准;最后,采用基于最小区域的叶片型线轮廓度误差评定方法进行误差评定。实验分析结果表明:改进方法相对于传统ICP算法,可在原有收敛值基础上达到进一步收敛的效果,轮廓度误差相对减小28.57%。该方法有效提高了叶片型线轮廓度误差评定的精确度,可为叶片的加工质量提供可靠判定。

To address the problem of poor registration precision of traditional iterative closest point(ICP) algorithm, an improved ICP algorithm was proposed.First, a new type line data registration method based on vector alignment was used, considering that the measured data of CMM show orderly array and one-to-one correspondence.Secondly, based on the traditional ICP algorithm, non-uniform rational B-spline(NURBS) curve fitting was carried out for the registration data, and then the adaptive particle swarm optimization(PSO) algorithm was used to further accurately register the measurement data.Finally, the evaluation method of blade profile error based on the minimum region was used to evaluate the accuracy.Experimental results show that, compared with the traditional ICP algorithm, the improved method can further converge on the original convergence value, and the contour error is reduced by 28.57%.This method can effectively improve the accuracy of the evaluation of blade profile error and provide a reliable basis for the evaluation of blade machining quality.